Topic

AI Governance & Trust

Guardrails, risk frameworks and responsible AI practices that let enterprises move faster safely.

Agentic AI

Mission-Critical AI Agents: The Architecture That Gets Them to Production

Most AI agent prototypes never become trusted production systems. LangChain Deployed Engineer Christine Manegan says the teams that succeed own their intelligence, from models and harness to evals and governance, and describes how an agent harness manages context, sub-agents and human-in-the-loop controls.

By The AI Enterprise Magazine Team ·

Data & AI Infrastructure

Why AI Fails Without Data Products and Data Contracts

AI stalls on old data problems that need a new fix, argues Actian CTO Emma McGrattan: treating data as a product and governing it with data contracts. She cites survey results linking company-wide data products to AI in production and offers a one-project way to start.

By The AI Enterprise Magazine Team ·

Agentic AI

AI Agent Sprawl: Why Enterprises Need an Agentic Control Plane

Building an AI agent is easy; running thousands of them is not. IBM's Ann Leach says agent sprawl creates security and cost risk, lists five questions an agentic control plane must answer and describes how Starlink coordinated procurement agents.

By The AI Enterprise Magazine Team ·

Security & Fraud

AI Agent Overreach: Why Enterprises Need Context-Based Controls

AI agents will overreach, and traditional security controls weren't built for probabilistic software, says Rubrik's Cal Al-Dhubaib. He offers real examples of agent overreach, a three-part model of context-based control and three questions every team should ask before AI fails.

By The AI Enterprise Magazine Team ·

Agentic AI

From Automation to Autonomy: Trusted Agentic AI Controls for Banks

Banks are using AI to rerun fixed chatbot workflows, not to act autonomously, according to Midships CEO Ajit Gupta. Checking each agent's purpose, objective, plan and API call, with signed human approvals, can keep autonomous agents on track, he says.

By The AI Enterprise Magazine Team ·

Agentic AI

Agentic AI in the Enterprise: From Human in the Loop to Agent Ops

Leaders from Revefi, Rhino Federated Computing, Precisely, AtScale and Google Cloud define what makes AI truly agentic and argue human review won't scale. Their alternative: human-on-the-loop oversight, two-tier governance, agents that govern agents and the rise of agent ops.

By The AI Enterprise Magazine Team ·

Agentic AI

Agentic Data Management: How AI Agents Let Analysts Self-Serve Data

Agentic data management pays off most for the analysts, data scientists and leaders stuck in the data team's queue, Matillion's field engineering team argues. Its Maia agent offers self-service pipeline building, permission prompts, context files that enforce standards and AI-driven troubleshooting.

By The AI Enterprise Magazine Team ·

Agentic AI

Five Questions Enterprises Must Answer to Scale Agentic AI, per IBM

IBM's Ryan Zombo lays out five questions enterprises must answer to move agentic AI into production, from avoiding agent sprawl to avoiding lock-in. Governance works like brakes on a race car, he argues, citing productivity results from IBM's internal client zero program.

By The AI Enterprise Magazine Team ·

Agentic AI

Custom MCP Servers and the Composable, Agentic Enterprise Platform

No one is closer to enterprise data than the integration platform, argues SnapLogic Senior Solutions Engineer Dylan Vetter. He explains how IT teams can share governed integration assets across business units and build custom MCP servers that connect LLMs to company data.

By The AI Enterprise Magazine Team ·

Data & AI Infrastructure

LLMOps at Scale: Deploying and Monitoring LLMs With HPE MLIS

In a 2024 AI Connect webinar, two HPE speakers said deployment, not training, had become the main hurdle for enterprise LLMs. They grouped the problems into technical, operational and security challenges and demoed HPE's inference software, including autoscaling and canary rollouts.

By The AI Enterprise Magazine Team ·

AI Strategy & ROI

Data Executives on AI: 5 Themes Heard at COLLIDE 2024

At COLLIDE 2024 in Atlanta, AI Connect co-founder Brian Mink outlined five themes from data executives: feeling behind on AI, board pressure, data strategy, human-centric AI and bias. His central point was that organizational practice has to catch up with the technology.

By The AI Enterprise Magazine Team ·

AI Governance & Trust

AI Governance: Layered Defenses and Guardrails, Per DataRobot

At COLLIDE 2024 in Atlanta, DataRobot's Jessica Lin said no single defense can govern generative AI, so enterprises should layer people, processes and auditability. She described model-agnostic governance, compliance documentation and guardrails that block risky inputs and outputs.

By The AI Enterprise Magazine Team ·

AI Governance & Trust

GenAI Data Privacy and Governance: Risk Tiering and Ethics Councils

In a 2024 AI Connect webinar sponsored by Daugherty Business Solutions, leaders from Meta, ADP, Verizon, BBDO and Daugherty discussed generative AI privacy, bias and governance. They described privacy by design, cross-functional ethics councils, risk tiering of use cases and continuous monitoring.

By The AI Enterprise Magazine Team ·

People, Culture & Leadership

Is ChatGPT Cheating? Panel on GenAI in K-12 Education

At the fourth annual AI Connect K-12 Data Science Conference in 2024, a panel of educators and data professionals said ChatGPT is a tool, not automatically cheating. They urged schools to teach citation, critical thinking and human oversight while teachers use AI to reduce workload.

By The AI Enterprise Magazine Team ·

AI Governance & Trust

AI in the Classroom: A 10-Point Bill of Rights for Schools

At the 2024 AI Connect K-12 Data Science Conference, Tracy Unified School District science teacher Michael Copass proposed 10 principles for AI in schools. They cover AI literacy, emotional deception, proof of effectiveness, transparent training data and parental opt-outs.

By The AI Enterprise Magazine Team ·

Security & Fraud

Automated Data Security: Self-Service Access to Sensitive Data

In a 2024 AI Connect webinar brought to you by Satori, leaders from Strata Decision Technology and Satori explained how to grant self-service access to sensitive healthcare and financial data. They stressed automation, access lanes, dynamic masking and tying permissions to tickets.

By The AI Enterprise Magazine Team ·

AI Governance & Trust

Generative AI Meets Responsible AI: Risks and Observability

At COLLIDE 2023 in Atlanta, Fiddler AI co-founder and CEO Krishna Gade outlined the risks of large language models, including privacy leaks, hallucinations, unreliable self-explanations and bias. He argued that AI observability is the missing link for deploying generative AI responsibly.

By The AI Enterprise Magazine Team ·

AI Governance & Trust

Generative AI Business Opportunities, Risks and Ethics: Panel

At COLLIDE 2023, a panel of data and AI leaders from Kellogg's, Nike, Randstad Enterprise and Stardog, moderated by Carter's, weighed generative AI's opportunities against bias, hallucinations and privacy risk. They urged AI principles, testing, human oversight and caution with company data.

By The AI Enterprise Magazine Team ·

Data & AI Infrastructure

Enterprise Architecture Lessons From 25 Years in Data: Vida Williams

At COLLIDE 2023 in Atlanta, Vida Williams of the Virginia Alcoholic Beverage Control Authority looked back on 25 years in data and enterprise architecture. She drew lessons on data modeling, executive attrition, data-driven culture and the slow ROI of data, then cautioned against tech for tech's sake in generative AI.

By The AI Enterprise Magazine Team ·

AI Strategy & ROI

AI Hype to Real Results: Aflac, Carter's and DataRobot Panel

At COLLIDE 2023 in Atlanta, analytics leaders from Aflac, Carter's, DataRobot and RXA @ OneMagnify discussed why AI projects stall and how to choose ones that pay off. They described feasibility tests, governance and ethics, and what they expected from generative AI at the time.

By The AI Enterprise Magazine Team ·

Security & Fraud

Human Inputs in AI Security: How Much Can You Trust Your Labels?

In a session at the Data Science Innovators Conference 2023, Samuel Zaruba Smith, a director at Bank of America, said human labels and annotations in supervised security AI are of questionable value and add less as systems improve. He described imbalanced threat data, human-driven failure modes and how to check unsupervised systems.

By The AI Enterprise Magazine Team ·

AI Use Cases & Applications

AI and the Decentralized Web: Web3 and Metaverse Outlook

In a session at the Data Science Innovators Conference 2023, Intel Chief Data Scientist Dr. Melvin Greer described how web3 infrastructure and the metaverse could move the web from consumption to creation. He urged AI practitioners to start experimenting with blockchain, NFTs and cryptocurrencies.

By The AI Enterprise Magazine Team ·